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Syntactic Pattern Recognition from Observations: A Hybrid Technique

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Bio-Inspired Computing and Applications (ICIC 2011)

Part of the book series: Lecture Notes in Computer Science ((LNBI,volume 6840))

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Abstract

This paper presents a novel technique for automated learning from observations. The technique arranges in a row four traditional pattern recognition approaches (numeric, logic, statistical and finally syntactic) within a unifying framework. Each processing step is conceived as a transformation of the input dataset from one state to another. The proposed technique considers measurable observations as inputs and produces a set of formal rules, i.e., a grammar, as final output. To this end, a four-state grammar induction process is described in detail by means of a step-by-step example. As a proof-of-concept for the feasibility of the proposal, references to early experimental validations are given. Finally, possible comparison with other well-known approaches are discussed.

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Author information

Authors and Affiliations

  1. DIASS, Polytechnic of Bari, Taranto, Italy

    Vincenzo Di Lecce & Marco Calabrese

Authors
  1. Vincenzo Di Lecce
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  2. Marco Calabrese
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Editor information

Editors and Affiliations

  1. School of Electronics and Information Engineering, Tongji University, 4800 Caoan Road, 201804, Shanghai, China

    De-Shuang Huang

  2. School of Computer and Communication Engineering, Zhengzhou University of Light Industry, No. 5, Dongfeng Road, Jinshui District, 450002, Zhengzhou, Henan, China

    Yong Gan

  3. School of Electrical, Computer & Telecommunications Engineering, University of Wollongong, 2522, P.O. Box, North Wollongong, NSW, Australia

    Prashan Premaratne

  4. School of Computer Science and Engineering, Inha University, 402-751, Inchon, Korea

    Kyungsook Han

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© 2012 Springer-Verlag Berlin Heidelberg

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Di Lecce, V., Calabrese, M. (2012). Syntactic Pattern Recognition from Observations: A Hybrid Technique. In: Huang, DS., Gan, Y., Premaratne, P., Han, K. (eds) Bio-Inspired Computing and Applications. ICIC 2011. Lecture Notes in Computer Science(), vol 6840. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24553-4_20

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  • DOI: https://doi.org/10.1007/978-3-642-24553-4_20

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-24552-7

  • Online ISBN: 978-3-642-24553-4

  • eBook Packages: Computer ScienceComputer Science (R0)

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